Enhanced Rolling Motion of Magnetic Microparticles by Turning Interface Lubrication
Yuke Li, Xiyue Liang, Zhuo Chen, Hongzhe Liao, Yue Zhao, Masaru Kojima, Qiang Huang, Tatsuo Arai
Abstract
Micro-nano robots must break the symmetry of the flow field to generate net displacement in the low Reynolds number environment. The spherical micro-robots utilize the frictional forces generated through interaction with the surface. We designed a magnetic microroller robot powered by the rotating AC magnetic field. Here, we employed dual measurements of laser ranging and computer vision to demonstrate that a single 100 μm microroller maintains a lubrication film of 1 to 15 μm with the surface during normal motion. We found that the translational velocity of the microroller is correlated with the lubrication film thickness. Based on the robot's gravity, we controlled an additional downward gradient magnetic field to effectively increase the load of robot and reduce the lubrication film thickness, thereby controllably increasing the translational velocity of the robot. For example, the gradient magnetic field generated by superimposing a 30mA direct current input can reduce the lubrication film thickness from 8 μm to 4 μm in a 10 Hz rotating magnetic field, and increase the translational velocity from 230 μm/s to 460 μm/s. The enhancement of the robot's motion performance enables it to better control its movement in fluids. Finally, we validated the strategy for controllable acceleration of micro-scale particles rolling on surfaces, applied to control fluid motion in multiple arteries within blood vessels. These results offer deeper insights into the physical motion mechanism of surface robots and hold significant implications for future applications in biomedical engineering.
BibTeX
@inproceedings{iros2025_enhancedrollingm,
title = {Enhanced Rolling Motion of Magnetic Microparticles by Turning Interface Lubrication},
author = {Yuke Li and Xiyue Liang and Zhuo Chen and Hongzhe Liao and Yue Zhao and Masaru Kojima and Qiang Huang and Tatsuo Arai and Xiaoming Liu},
booktitle = {IROS 2025},
year = {2025}
}